Doctoral Dissertation Research in Economics: Reference-Dependent Effort Provision under Heterogeneous Gain Loss Attitudes

经济学博士论文研究：异质得失态度下的参考依赖努力供给

• 批准号: 1949517
• 负责人: Isabel Trevino
• 金额: $ 2.3万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2022-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1949517&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Economics; Reference

Understanding how individuals make decisions in the face of uncertainty is a core issue in economic research. While earlier economic theory postulated full rationality, researchers have advanced upon these classical models by introducing the idea of reference-dependent decision making. These models, rooted in the intuition that individuals compare their outcomes to some reference point, have been used in a number of contexts, ranging from the putting behavior of professional golfers (Pope and Schweitzer, 2011) to the job search behavior of unemployed workers (DellaVigna et al, 2017). The original reference-dependent models suffered from one major drawback, however: in failing to specify a fixed reference point, they left open a substantial degree of freedom. Theoretical advancements sought to shut this downfix this problem, culminating in models of expectations-based reference dependence (notably, Koszegi and Rabin, 2006 – KR). By endogenizing the reference point as rational expectations, this model generated new and, testable implications, garnering mixed experimental support. However, these prior studies are potentially confounded by an assumption of universal loss aversion, in which outcomes falling below the reference point are assumed to feel worse than those above the reference point. Contrary to this assumption, empirical and experimental evidence suggests that roughly 30% of individuals are instead “gain -loving”.” Importantly, prior work by the authors suggests that a small minority of gain -loving participants can skew aggregate predictions of the model (Goette et al, 2019). In this project, the research team will provide additional evidence of how heterogeneity in these gain-loss attitudes confounds tests of KR, and design an experimental paradigm to overcome these confounds in the context of effort provision. A better understanding of the distribution of gain-loss preferences is particularly important when considering a number of key policy questions, as these reference-dependent models have proven to be invaluable in settings such as unemployment insurance and health insurance decisions.In order to accomplish the stated goals, this project will focus on updating an existing experimental paradigm so as to account for the confound ofthat is heterogeneity in gain-loss attitudes. A two-stage experiment is thus proposed, wherein a measure of the participant’s gain-loss attitude is recovered from first stage choices, and the hypothesis is tested in the second. Specifically, participants will first be asked questions of the form: “How many tasks are you willing to work at wage X?”. The wages will either be deterministic (e.g. 20 cents per task) or stochastic (e.g. with 50% chance, the wage will be 10 cents per task and with 50% chance it will be 30 cents per task). This variation will allow the authors to build a structural model and recover the key behavioral parameter of gain-loss attitudes alongside a cost of effort function. Participants are asked a slightly different question in the second stage, adapted from Abeler et al (2011): “How much are you willing to work if your wage is a 50% chance of 25 cents per task, and a 50% chance of Y dollars regardless of the number of tasks?”. The key treatment will be randomly varying Y from a small ($5) to a large amount ($20). KR predicts that loss averse agents should work harder as Y increases, while gain loving agents should work less hard. By using the previously measured gain-loss attitude, this project is able to directly test whether individuals with different preferences respond differently as predicted by the theory. The resulting evidence will help clarify the mixed results from the prior paradigm, as well as providing evidence of whether KR is predictive of behavior after controlling for the confounding heterogeneity in gain-loss attitudes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

了解个体如何在不确定性面前做出决策是经济学研究的核心问题。虽然早期的经济理论假设完全理性，但研究人员通过引入参考依赖决策的思想，在这些经典模型上取得了进展。这些模型植根于个人将其结果与某个参考点进行比较的直觉，已被用于许多背景下，从职业高尔夫球手的推杆行为（Pope和Schweitzer，2011）到失业工人的求职行为（DellaVigna等人，2017）。然而，最初的参考依赖模型有一个主要缺点：由于没有指定一个固定的参考点，它们留下了相当大的自由度。理论上的进步试图解决这个问题，最终形成了基于预期的参考依赖模型（值得注意的是，Koszegi和Rabin，2006 - KR）。通过将参考点内化为理性预期，这个模型产生了新的、可检验的含义，获得了混合的实验支持。然而，这些先前的研究可能被普遍的损失厌恶假设所混淆，在这种假设中，低于参考点的结果被认为比高于参考点的结果更糟糕。与这一假设相反，经验和实验证据表明，大约30%的人是“喜欢收获的”。重要的是，作者之前的工作表明，少数喜欢获得的参与者可能会扭曲模型的总体预测（Goette et al，2019）。在这个项目中，研究小组将提供更多的证据，这些得失态度的异质性如何混淆KR的测试，并设计一个实验范式，以克服这些混淆的努力提供的背景下。在考虑一些关键的政策问题时，更好地理解收益-损失偏好的分布尤为重要，因为这些依赖于参考的模型已被证明在失业保险和医疗保险决策等环境中是非常宝贵的。该项目将侧重于更新现有的实验范式，以解释得失态度的异质性。因此，提出了一个两阶段的实验，其中的参与者的得失态度的措施是从第一阶段的选择恢复，并在第二个假设进行测试。具体来说，参与者将首先被问到以下问题：“你愿意以X工资工作多少任务？"。工资将是确定性的（例如，每个任务20美分）或随机的（例如，50%的机会，工资将是每个任务10美分，50%的机会，它将是每个任务30美分）。这种变化将允许作者建立一个结构模型，并恢复得失态度的关键行为参数以及努力成本函数。在第二阶段，参与者被问到一个稍微不同的问题，改编自Abeler et al（2011）：“如果你的工资是50%的机会每项任务25美分，50%的机会Y美元，无论任务数量如何，你愿意工作多少？”。关键的处理将是随机地改变Y，从小（$5）到大（$20）。KR预测，当Y增加时，厌恶损失的代理人应该更加努力地工作，而喜欢收益的代理人应该不那么努力。通过使用先前测量的得失态度，该项目能够直接测试具有不同偏好的个体是否如理论所预测的那样做出不同的反应。由此产生的证据将有助于澄清混合结果从先前的范式，以及提供证据，是否KR是预测的行为后，控制的混杂异质性的得失attitudes.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。